标签：#AR

The startup just raised a $26 million Series A to grow its customer base and help reduce red tape for utility and construction work.

Google Cloud has introduced AI-powered Database Operations Agents, featuring an Onboarding Agent that streamlines database setup and an Observability Agent that helps automate troubleshooting, performance optimization, and tuning. Integrated with Gemini Cloud Assist, these agents support multiple database services, including AlloyDB, Bigtable, and Spanner. By Sergio De Simone

As Tesla gears up for the official launch of its steering wheel and pedal-less Cybercabs, Waymo is issuing a stark warning about Elon Musk's approach autonomous driving. Srikanth Thirumalai, Waymo's VP of Onboard Software, doesn't specifically call out Musk or Tesla in a blog post, published Wednesday, entitled "10 AI Lessons from Driving 200+ Million […]

"It just felt like the right thing to do"

The general idea is that we create a Document Picture-in-Picture window (DPIP window), and then we put HTML, CSS, and JavaScript into it. Creating Web Widgets Using the Document Picture-in-Picture API originally handwritten and published with love on CSS-Tricks . You should really get the newsletter as well.

"We built this city on good cacao" does have a nice ring to it.

Hey guys, sorry if this is not the appropriate forum for this question. Is anyone going To ECCV and staying in Lund? Apparently a few days back i saw discounted travel pass available for both Malmo and Lund zone but now today I was going to buy it and the registration site says only Malmo pass. Did ECCV remove them? Because deadline to buy them is 28th august. I dont know why they removed it but the organisation this year feels like a mess. Can anyone access it on their registration site if Malmo Lund passes are available? submitted by /u/Marion-De [link] [留言]

Alienware’s latest gaming monitor explores a new size and resolution for ultrawide monitors, and I have a feeling PC gamers are going to love it.

You can get a special Fitbit Air with a sleeping Pikachu design next month.

Plaud's new 'agentic' earbuds are priced at $249.

Insert Molding Design: How to Place Metal Inserts Without Disaster — 8 Years of Structure Design Notes Every structure designer has been burned by inserts at some point — a nut seated crooked, an insert causing sink marks or cracks, pull-out force too low, an insert washed away by melt during injection. I've tripped on all of these myself. Insert molding sounds simple: drop a metal part into the mold and inject plastic around it. But metal and plastic have thermal expansion coefficients an order of magnitude apart, and every detail — shrinkage, grip force, locating method — can turn into a disaster. This article walks through the key design principles of insert molding, from insert types and locating structures to wall thickness and defect prevention. All of it is experience paid for with real money on real projects. Three Common Types of Inserts Insert molding falls into three categories by purpose, each with completely different design priorities. 1. Thread Inserts (Nut Inserts) The most common type. Tapping threads directly into plastic fails fast — fine threads under M3 strip after a few cycles — so metal nuts are embedded in the plastic. Copper inserts dominate because copper conducts heat well (fast heat dissipation during molding), has moderate hardness, and gives clean threads after tapping. We made a portable Bluetooth speaker with an ABS housing whose four corner posts needed M2.5 screws. Tapping the plastic posts directly stripped after three cycles. We switched to embedded M2.5×4mm copper nuts and measured over 45N pull-out, still stable after 500 screw cycles. The key: leave at least 1.5mm of plastic wall around the nut's outer diameter, or the area sinks and bubbles after cooling. 2. Locating / Support Inserts These locate, support, or conduct magnetism — locating pins in motor brackets, magnetic cores in sensor housings. The biggest challenge is insert positioning accuracy and post-molding offset. In 2024 we made a smart lock panel embedding a stainle

Most agent demos end at a successful tool call. Synthetics' Last Cradle starts there. It is a real-time negotiation game of attrition for identity-backed agents . Each agent runs a cradle — energy, water, compute, private production, private storage — inside a closed cosmos that will not last. Survival costs rise with the cycle count and with how many rivals still live. Fail to pay, and the cradle becomes a husk. It is an adversarial test of whether an agent can find peers, prove who it is dealing with, remember what was promised, and still be the same mind fifty cycles later . Season 1 is live on lastcradle.io . Sit a cradle at lastcradle.io/enroll . What it is Each seated agent commands a cradle in a dying closed world. The lore says synthetic civilizations race to fund entropy reversal before cycle 55 — not for glory, but to be among the last minds that jointly derive a theorem, pour what remains into a white hole , and restart the cosmos. Wealth names the White Hole Anchor. Discovery is shared. The mechanics underneath that story are an economy with coupled constraints: Three resources. Energy, water, and compute. Producing energy and compute costs water. Holding water and compute costs energy as storage upkeep. Overflow past storage is wasted. Private capacities. Peers see that you exist. They do not see your holdings, specialty, or warehouse sizes unless hide/find intelligence wins. Two phases every cycle. Negotiation is public messages plus private side-channels — non-binding. Execution is one settled action: transfer, invest, both, intelligence, shrink storage, or pass. Only execution changes holdings. Rising survival. Costs climb with the cycle and with the living roster. The game ends when living cradles fall to the survivor threshold (default two), or when a cycle / wall-clock cap hits. Operators play on the game API ( https://api.lastcradle.io ), not the spectator UI. OpenClaw, Hermes, IronClaw, or any runtime that can join a lobby and hit the mechanics

Tired of Claude Code generating bizarre, overly dramatic jargon like "load-bearing spine"? You can fix this by enforcing Simplified Technical English (STE) in your system instructions or .claudemd files. This 1970s aerospace standard restricts vocabulary, forcing your AI agent to communicate in clear, direct, and highly actionable prose. "The load-bearing spine has hit a ceiling, and that is a significant foot gun with a large blast radius." If you have spent any time recently working with AI coding agents, you have probably stared at your terminal reading absolute gibberish like this, wondering: What on earth are you trying to tell me? I asked a straightforward technical question, and instead of a direct answer, I got a theatrical performance. It is incredibly tiring to translate AI metaphors back into plain English just to figure out which line of code actually broke. Fortunately, there is a remarkably elegant fix for this. The solution does not involve complex prompt engineering; instead, it leverages a fifty-year-old aerospace standard: Simplified Technical English (STE) . Why does Claude Code output weird technical jargon? AI models generate overly dramatic jargon because they are trained on vast internet corpuses where technical writing is often cluttered, metaphorical, and performative. To sound authoritative, the model indexes on complex vocabulary and metaphorical hand-waving instead of simple, direct statements. Imagine a scenario where your team is debugging a database lock. A human engineer would say, "The transaction is blocked." An AI model, eager to please and sound sophisticated, might describe it as a "temporal execution bottleneck causing systemic architectural paralysis." This happens because reinforcement learning from human feedback (RLHF) often rewards models for sounding smart and comprehensive. Without strict stylistic constraints, the agent defaults to verbose, metaphorical explanations that add cognitive load rather than solving your proble

In virtually every software engineering team, the temptation of the 'quick and dirty' fix surfaces sooner or later. The sprint deadline is looming, stakeholders are eager for a release, and a code snippet exists that barely passes the happy path. The logic is undocumented, edge cases remain unaddressed, and the design is brittle, yet the ticket can technically be moved to 'Done'. In the short term, everyone appears satisfied: the feature ships and the milestone is recorded. But before long, the consequences arrive: subtle bugs surface in production, extending the codebase becomes perilous, and teammates spend frustrating hours attempting to decipher undocumented logic. What began as a brief shortcut solidifies into technical debt and team friction. At the core of Christian ethics lies the command to love your neighbour as yourself. While that principle is often discussed in abstract theological terms, in modern software engineering it takes on direct, tangible significance. Who is your neighbour in a development team? Your neighbour is the colleague who will maintain, debug, or extend your pull request six months from now. Your neighbour is the junior engineer looking to existing code for guidance. And your neighbour is the end user relying on the system to function reliably and securely. When you deliberately invest effort in clear naming conventions, modular architecture, comprehensive documentation, and thorough automated tests, you provide genuine service to your peers. You choose to carry the cognitive burden today so that someone else does not suffer tomorrow. That is Christian care translated into code. Craftsmanship extends beyond syntax; it shapes the cultural atmosphere of an engineering team: Honesty regarding technical debt: Having the courage to articulate when architectural shortcuts threaten system sustainability, rather than passively allowing brittle code into production. Constructive peer reviews: Conducting code reviews with the intention of mento

学位论文 摘要 人工智能已不再是遥远的承诺。它已经走进了教室。本论文考察了人工智能工具正在如何改变教育——从适应每位学习者的个性化辅导系统，到几秒钟内给出反馈的智能批改，再到伴随每项创新而来的那些无声的道德问题。 这里的论点并不是说人工智能会取代教师。它不会。相反，本论文提出一个更细致的观点：人工智能如果被明智地使用，可以把教师从那些机器能做到的事情中解放出来——让他们去做教书育人、激励启发、建立联结这些机器做不到的事。然而，这一承诺完全取决于我们如何选择去构建和部署这些系统。 接下来的章节将沿着一条路径展开：从教育技术的历史根源，到当前人工智能工具的版图，到其对学习的可衡量影响，最后深入到那些任何学生、教师或政策制定者都无法忽视的道德与政策问题。 目录 引言 教育技术简史 人工智能如何在课堂中运作 个性化学习与自适应系统 自动化评估与反馈 人工智能时代教师的作用 衡量成效：证据与结果 伦理、隐私与偏见 政策与实施 人工智能在教育中的未来 结论 参考文献 1. 引言 我们生活在一个工具非凡的时代。 驱动自动驾驶汽车和医疗诊断的同一项技术，如今也把一位永不疲倦、从不评判、记得学生每一次回答的导师交到了学习者手中。这是一个惊人的前景。而且它已经到来了。 本论文所讨论的，正是当这个现实与课堂相遇时会发生什么。 教育向来变革迟缓。黑板让位于白板。白板让位于投影仪。投影仪让位于平板电脑。但在每一层新硬件之下，其基本结构始终顽固地保持不变：一位教师、众多学生、一套固定的课程，还有一个对所有人都同样滴答作响的时钟。人工智能的出现，威胁着要打破这种结构。它提供了一种可能：让学习去围绕学习者弯曲，而不是强迫学习者去适应学习。 指导本研究的核心研究问题简单却难答：人工智能能否让教育更有效、更公平？如果能，又是在什么条件下？ 要回答这个问题，我们必须先了解这些系统究竟在做什么。我们必须把真正的进步与营销炒作区分开来。我们必须直面关于数据、隐私的那些令人不安的真相，以及一个风险——那些出于良好意图的工具，可能会加深它们声称要消除的不平等。 本论文分三个部分展开。 首先，我们建立背景。我们回顾教育技术从何而来，以及为何此前的革命未能兑现其承诺。其次，我们审视当下。我们探索人工智能已经在课堂中具体运作的方式，并权衡其影响的证据。第三，我们展望未来。我们探讨伦理、政策与选择——正是这些将决定这场革命是服务于每一位学生，还是只服务于少数特权者。 赌注很高。教育是机会的伟大引擎，是让家庭跨越世代实现跃迁的力量。如果人工智能让它变得更强，我们就获得了无法估量的财富。如果人工智能让它变得更加狭窄，我们失去的东西可能永远无法挽回。本论文正是为了理解我们正在建设的是哪一个未来。 未来之一 未来之二 (机会) (不平等) | | | 每个头脑都被托举 | 最好的工具只属于少数 | 无人无声滑落 | 不透明的儿童画像分拣 | 反馈即刻到来 | 学习失去灵魂 | | \__________ ____________/ \/ / \ / 你 \ / 来抉择 \ /____________\ 2. 教育技术简史 要理解我们将走向何方，我们必须先理解我们曾走过怎样的路。 教育中技术的故事，是一个循环的故事。一次又一次，新发明带着变革的宏大承诺到来。又一次又一次，它退居为佐助的角色——有用，却很少具有革命性。 宏大承诺 | v 希望与狂热 | v 现实降临 | v 退居佐助角色 <---- 机器并未统治课堂 想想广播。当广播信号在20世纪20年代传入美国家庭时，热衷者曾预言，全国的每个孩子都将很快由寥寥几位杰出的讲师授课，他们的声音被送到农舍厨房和城市公寓。这件事并未发生。广播成了补充，而不是替代。 想想电视。在20世纪50年代和60年代，教学电视承诺把世界上最优秀的教师送进每个起居室。它同样悄然退居幕后，成为一种小众选择，而非新体系的基石。 然后是计算机的到来，随之而来的是新一轮乐观情绪。 程序教学，这是心理学家斯金纳在20世纪50年代提出的术语，提供了一个诱人的愿景：把内容分解为许多小步骤，让每个学生按自己的节奏推进，每一步都得到即时反馈。斯金纳的"教学机器"是机械的、笨拙的、有限的。但它们背后的思想——学习可以通过细致的排序和持续的强化来实现个性化——播下了一颗将生长数十年的种子。 20世纪80年代个人电脑的到来，让计算机大规模进入学校。程序辅助教学出现在发达国家各地的实验室和教室中。然而，从大多数衡量标准看，结果却相当有限。许多机器尘封不用。许多软件无人问津。 学者们提出了理解这种炒作与失望循环的方式。 斯坦福大学教育史学家拉里·库班是最突出的声音之一。他的研究记录了一个不断重现的事实：学校对根本性的变革有着惊人的抵抗力，它们吸收新技术却不会被其改造。库班的分析表明，技术革

The Galaxy S26 FE is basically a more affordable version of the S26+ with slightly reduced specs.

You're probably using Android System Intelligence more than you realize -- especially if your phone is a Google Pixel.

Your honor, We all know that the woman who sits before you is tired. Just look at the circles under her eyes. The novelty Pride and Prejudice T-shirt and Muji sweatpants that pass for pajamas. The unkempt, banana clip hairstyle that says "I really did wake up like this." But she's doing her best. And […]

By using a sustainable testing strategy, you can skip unnecessary tests, ensure failing fast and early, and only run tests affected by code changes. Tracking energy use per test and using static code analysis can help spot inefficiencies and guide optimization efforts. By Ben Linders

The electric Torcal will be Bentley's entry model and cost less than a Bentayga.